Roadways pose a significant challenge to landscape functioning and connectivity, resulting in habitat loss, degradation, and a threat to the persistence of species that are affected by roadways. Although many conservation network plans acknowledge the negative effects roads can have on connectivity, few have thoroughly assessed and developed approaches to mitigate barrier and mortality effects of roads that fall within ecological networks. In southern California, the landscape-scale network approach has been adopted in response to the widespread habitat conversion and fragmentation that has resulted from development in the region. The overarching goal of these plans is to preserve biological diversity through the conservation and management of functional habitats and linkages, which often requires identifying and mitigating the impact of roadways on the preserve network. To address these issues, we leveraged survey and monitoring data from an area in central San Diego County, producing a data-informed connectivity plan for a suite of focal species combined with an assessment of structural connectivity. In addition to designing linkages among conserved areas, we identified 33 target road crossing locations at the intersection of modeled movement paths and major roadways based on the density of potential crossing points assembled from six focal species.
Once a general location for the crossing was selected, we reviewed local information to guide specific site and design recommendations. To do so, we explored site characteristics using terrain data, street-view in Google Earth, information from prior data collection, and location knowledge. We categorized the size and type of species to be considered in the design of each structure and used a comprehensive literature review on wildlife crossing structure evaluations and guides to make initial recommendations on structure sizing and type. We then estimated the minimum length of fencing necessary based on the literature and site conditions. To aid decision-making regarding wildlife crossing structure improvement, we categorized each recommendation using two prioritization criteria: 1) importance to wildlife, and 2) type of improvement (i.e., major or minor). The first was focused on the importance of each site to the suite of wildlife we considered in our analyses whereas the second prioritization was included to allow transportation agencies to identify opportunities for near-term improvements based on whether existing crossings could be enhanced through minor alterations, such as clearing of sediment and debris in existing crossing structures. Although this study is an example of only the first step in the process for developing a fully scoped wildlife crossing infrastructure plan, such data-informed infrastructure recommendations combining complementary modeling and field-based data are critical for effective planning for wildlife crossing structures.